use of simulation software in services industry

INTRODUCTION

 based on the process of modeling a real phenomenon with a set of mathematical formulas. It is, essentially, a program that allows the user to observe an operation through simulation without actually performing that operation. Simulation software is used widely to design equipment so that the final product will be as close to design specs as possible without expensive in process modification. Simulation software with real-time response is often used in gaming, but it also has important industrial applications. When the penalty for improper operation is costly, such as airplane pilots, nuclear power plant operators, or chemical plant operators, a mockup of the actual control panel is connected to a real-time simulation of the physical response, giving valuable training experience without fear of a disastrous outcome.

Advanced computer programs can simulate power system behavior, weather conditions, electronic circuits, chemical reactions, mechatronics, heat pumps, feedback control systems, atomic reactions, even complex biological processes. In theory, any phenomena that can be reduced to mathematical data and equations can be simulated on a computer. Simulation can be difficult because most natural phenomena are subject to an almost infinite number of influences. One of the tricks to developing useful simulations is to determine which are the most important factors that affect the goals of the simulation.

why to use simulation modeling?

Simulation modeling solves real-world problems safely and efficiently. It provides an important method of analysis which is easily verified, communicated, and understood. Across industries and disciplines, simulation modeling provides valuable solutions by giving clear insights into complex systems.

 Simulation enables experimentation on a valid digital representation of a system. Unlike physical modeling, such as making a scale copy of a building, simulation modeling is computer based and uses algorithms and equations. Simulation software provides a dynamic environment for the analysis of computer models while they are running, including the possibility to view them in 2D or 3D.

The uses of simulation in business are varied and it is often utilized when conducting experiments on a real system is impossible or impractical, often because of cost or time.

The ability to analyze the model as it runs sets simulation modeling apart from other methods, such as those using Excel or linear programming. By being able to inspect processes and interact with a simulation model in action, both understanding and trust are quickly built.

benefits of using simulation software

1      risk-free environment

Simulation modeling provides a safe way to test and explore different “what-if” scenarios. The effect of changing staffing levels in a plant may be seen without putting production at risk. Make the right decision before making real-world changes.

2 save money and time

Virtual experiments with simulation models are less expensive and take less time than experiments with real assets. Marketing campaigns can be tested without alerting the competition or unnecessarily spending money.

3 visualization

Simulation models can be animated in 2D/3D, allowing concepts and ideas to be more easily verified, communicated, and understood. Analysts and engineers gain trust in a model by seeing it in action and can clearly demonstrate findings to management.

4 insight into dynamics

Unlike spreadsheet- or solver-based analytics, simulation modeling allows the observation of system behavior over time, at any level of detail. For example, checking warehouse storage space utilization on any given date.

5 increased accuracy

A simulation model can capture many more details than an analytical model, providing increased accuracy and more precise forecasting. Mining companies can significantly cut costs by optimizing asset usage and knowing their future equipment needs.

6 handle uncertainty

Uncertainty in operation times and outcome can be easily represented in simulation models, allowing risk quantification, and for more robust solutions to be found. In logistics, a realistic picture can be produced using simulation, including unpredictable data, such as shipment lead times

General simulation

General simulation packages fall into two categories:

 discrete event and continuous simulation. Discrete event simulations are used to model statistical events such as customers arriving in queues at a bank. By properly correlating arrival probabilities with observed behavior, a model can determine optimal queue count to keep queue wait times at a specified level. 

Continuous simulators are used to model a wide variety of physical phenomena like ballistic trajectories, human respiration, electric motor response, radio frequency data communication, steam turbine power generation etc. Simulations are used in initial system design to optimize component selection and controller gains, as well as in Model Based Design systems to generate embedded control code. Real-time operation of continuous simulation is used for operator training and off-line controller tuning